3D Human Body Action Identification of Sports Based on Artificial Intelligence
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-97874-7_94
Reference10 articles.
1. Liang, C., Qi, L., He, Y., et al.: 3D human action recognition using a single depth feature and locality-constrained affine subspace coding. IEEE Trans. Circuits Syst. Video Technol. 28(10), 2920–2932 (2018)
2. Ding, W., Liu, K., Biao, X.U., et al.: Skeleton-based human action recognition via screw matrices. Chin. J. Electron. 26(04), 128–134 (2017)
3. Chen, C., Jafari, R., Kehtarnavaz, N.: A survey of depth and inertial sensor fusion for human action recognition. Multimedia Tools Appl. 76(3), 4405–4425 (2015). https://doi.org/10.1007/s11042-015-3177-1
4. Dong, M., Fang, Z., Li, Y., et al.: AR3D: attention residual 3D network for human action recognition. Sensors 21(5), 1656–1657 (2021)
5. Rodrigues, A., Pereira, A.S., Rui, M., et al.: Using artificial intelligence for pattern recognition in a sports context. Sensors 20(11), 3040–3041 (2020)
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